Triple

T8694791
Position Surface form Disambiguated ID Type / Status
Subject Earth Simulator E206380 entity
Predicate locatedInCity P40 FINISHED
Object Yokohama E10676 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Yokohama | Statement: [Earth Simulator, locatedInCity, Yokohama]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Yokohama
Context triple: [Earth Simulator, locatedInCity, Yokohama]
  • A. Yokohama chosen
    Yokohama is Japan’s second-largest city and a major international port located just south of Tokyo.
  • B. Nagoya
    Nagoya is a major industrial and commercial city in central Japan, known as a manufacturing hub and the capital of Aichi Prefecture.
  • C. Tokyo
    Tokyo is Japan’s largest metropolis and a global center of finance, culture, technology, and transportation.
  • D. Sendai
    Sendai is the largest city in Japan’s Tōhoku region, known for its lush greenery, historic sites, and status as a major economic and cultural center in northeastern Honshu.
  • E. Osaka
    Osaka is Japan's third-largest city and a major economic, cultural, and historical hub known for its vibrant street food, bustling nightlife, and role as a commercial center in the Kansai region.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69ca83555b6c8190abe930dd397e863b completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc58284c58819091beb05a7d6b3a1b completed March 31, 2026, 11:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69d02f4d26ec8190baacf68b7e6ca0eb completed April 3, 2026, 9:21 p.m.
Created at: March 30, 2026, 6:33 p.m.